Many classical data processing techniques rely on the representation and computation of
vector and matrix forms, where the vectorization or matricization is often employed on …

Given a huge, online stream of time-evolving events with multiple attributes, such as online
shop** logs:(item, price, brand, time), how can we summarize large, dynamic high-order …

This paper undertakes a comprehensive investigation of electricity price forecasting
methods, focused on the Irish Integrated Single Electricity Market, particularly on changes …

Many web applications, such as search engines and social network services, are
continuously producing a huge number of events with a multi-order tensor form,{count; …

Given an extensive, semi-infinite collection of multivariate coevolving data sequences (eg,
sensor/web activity streams) whose observations influence each other, how can we discover …

Time series subsequence clustering is a useful tool for recognizing dynamic changes and
uncovering interesting patterns in time series, and it can also be applied to downstream …

Large quantifies of online user activity data, such as weekly web search volumes, which co-
evolve with the mutual influence of several queries and locations, serve as an important …

Given an extensive, semi-infinite collection of multivariate coevolving data sequences,
whose observations influence each other, how can we discover the interpretable time …

論文抄録 複数の属性 (乗車時間, 乗車エリア, 降車エリア, タクシーの種類, 顧客の属性…)
を含むタクシー乗車データなどに代表される, 時間情報をともなうイベント集合は …

論文抄録 Web 検索履歴等に代表される大規模時系列データは, 時刻や地域,
キーワードといった様々な情報とともに収集され, テンソルストリームとして扱うことができる. Web …